Senior Manager - Analytics Products and Technology (Hyderabad)

Senior Manager, Analytics Products and Technology - Obesity Career Category Engineering Senior Manager, Analytics Products & - Technology Obesity Intelligence & - Analytics | Amgen India Reports to: Director, Technology, Operations & - Data Enablement Role Summary This is an India-based global role supporting Amgen's global obesity business. The Senior Manager, Analytics Products & - Technology will own the development and evolution of business-facing products that enable leaders to move from insight to action with clarity and speed. It is a product leadership role at its core - requiring solid judgment, technical fluency, and a deep understanding of how leaders make decisions. The focus is on creating products that simplify complexity, accelerate decisions, and meaningfully improve how the organization operates. This leader's mandate is to build products that serve as critical enablers of how the business plans, prioritizes, and executes. This leader will shape their direction, ensure they evolve with the needs of the organization, and drive adoption in a way that makes them indispensable to everyday work. The role also plays a key part in advancing AI-enabled capabilities and intelligent automation across the organization. As new opportunities emerge, this leader will help bring them to life in a way that is practical, scalable, and grounded in real business impact - ensuring that innovation translates into meaningful change, not experimentation for its own sake. Success is measured by products that become part of how the business runstrusted, widely adopted, and consistently making work faster, simpler, and more effective. Key Responsibilities 1. Product Strategy, Roadmap & - Technology Prioritization Own the product roadmap for Gateway, SKU Solver, and related decision-support capabilities, ensuring each product solves a real business problem and earns a place in everyday work. Shape user journeys, requirements, backlogs, release plans, value measures, and success criteria that connect product work to business decisions. Prioritize with discipline, balancing user value, technical feasibility, adoption potential, speed, risk, and long-term maintainability. Bring structure to ambiguity so teams understand what is being built, why it matters, and how it will change the way the organization plans, prioritizes, or executes. 2. Product Discovery, Design & - User Experience Work closely with leaders, analytics teams, and end users to understand how decisions are made today and where products can remove friction. Turn complex workflows into simple product concepts, intuitive experiences, and practical solution designs that help users move from insight to action. Challenge requests that add complexity without value, and redirect teams toward solutions that are useful, scalable, and easy to adopt. Partner with design, engineering, data, analytics, and business teams to test assumptions early and refine solutions before significant build effort is committed. Keep the user experience central. The best product is not the one with the most features; it is the one people trust and use. - Tool Delivery, Build Execution & - Release Management Lead delivery of business-facing tools, product enhancements, dashboards, workflow applications, and reusable capabilities from concept through release. Ensure solutions are secure, reliable, supportable, documented, and aligned with enterprise technology standards before they scale. Manage delivery trade-offs clearly, keeping momentum without sacrificing quality, usability, maintainability, or stakeholder trust. Build the muscle for repeatable delivery so new products and enhancements move faster over time without creating unnecessary bureaucracy. - AI-Enabled Solutions & - Intelligent Automation Serve as the first-line product lead for practical AI-enabled tools and intelligent automation opportunities until a dedicated AI capability is established. Help teams frame the business problem, define the desired outcome, identify required inputs, and determine whether AI or automation is the right solution. Coordinate with data science, technology, privacy, security, legal, compliance, and business partners to prototype and deploy custom solutions responsibly. Apply appropriate guardrails for documentation, validation, human oversight, user training, responsible use, and ongoing support. Focus on useful AI. The goal is not experimentation for its own sake; it is work that becomes faster, simpler, higher quality, or more scalable. - Adoption, Value Realization & - Product Operations Own product adoption plans, usage metrics, feedback loops, training support, release communications, and value realization tracking. Listen to users after launch. Understand where tools create leverage, where they create friction, and where process or behavior change is needed. Use evidence to sharpen priorities, retire low-value features, improve existing capabilities, and scale what proves .